Eyanhe/LFTC_Dataset_And_Checkpoints

LFTC: datasets and checkpoints

Uploaded and content-verified.

This is the large-asset companion to NLP-Course-Project-LFTC. Code, reports, figures, PowerPoint, Excel, metrics and per-example predictions are in GitHub.

The local snapshot contains 2,044 asset files, 56,530,278,162 bytes. Files under artifacts/ retain their original project-relative paths, including datasets, prepared inputs, pretrained models, final/local checkpoints and feature bundles. Historical .cache/ candidate checkpoints are stored under artifacts/legacy-candidates/, since the Hub reserves .cache/ paths. artifact-manifest.json records paths, sizes, SHA256 values and verification status.

Restore

hf download Eyanhe/LFTC_Dataset_And_Checkpoints --repo-type dataset --local-dir ../lftc-assets

Merge the downloaded files into the GitHub project root according to the manifest's original path field. In particular, restore artifacts/legacy-candidates/ to the original .cache/ directory; other artifacts/ paths map directly to the project root. The snapshot covers files actually present on the local workstation; it does not claim that every checkpoint produced on the training cluster has been downloaded.

Provenance and scope

The study has 428 completed v3 records, including 232 current-research records, 226 with V metrics and 42 fixed models with formal Q evaluations. These counts describe experiments, not a promise of 428 complete checkpoint folders. The original 2,859-item matrix was not fully executed.

Each original dataset and pretrained model retains its own source-specific license. The mixed collection is not relicensed under one blanket license. Original asset locks and model/readme metadata are retained at their corresponding paths and in GitHub. Local credentials, runtimes, private cluster-login helpers, regenerable MinHash work cache and duplicate transfer archives are outside this publication.